1. Field of the Invention
The present invention is directed to a radio communications receiver and more particularly to a radio communications receiver which detects radio signals and recovers data representative of the radio signals in the presence of interfering signals. The present invention is also directed to a method of receiving radio signals and recovering data representative of the radio signals in the presence of interfering signals.
2. Description of the Prior Art
In data and signal processing applications, it is often required to factorize a matrix of signal samples to provide a factor matrix having particular characteristics. For example, a desired factor matrix may be upper triangular or lower triangular in that the lower or upper part of the matrix may be filled with zeros. As a result, the factorized matrix may be interpreted as a set of simultaneous equations with these equations being solved in a manner facilitated by the upper or lower triangular form.
An example of where such matrix factorization is required is in radio communications receivers, and particularly in radio communications receivers which are arranged to detect radio signals and generate data from these radio signals in the presence of contemporaneously detected interfering signals. Such is the case with radio systems arranged to operate with code division multiple access. Code division multiple access is a radio communications technique in which data to be communicated is combined with a spreading code in some way before being modulated onto a radio frequency carrier signal. At the receiver, the radio signals are detected and the data is recovered by de-spreading the radio signals with knowledge of the spreading code used at the transmitter to form the radio signals. As a result of the spreading of the data, the receiver is able to generate a gain in the power of the detected signal, with respect to noise and other signals, for the wanted signal. As such, signals from a number of transmitters may be contemporaneously transmitted using different spreading codes and separated at corresponding receivers to the effect that the data which the radio signals represents may be recovered in spite of the presence of the interfering signals from the other transmitters. However, to detect the data from a wanted radio signal, the receiver must reject the unwanted signals which are contemporaneously detected with the wanted signal. As such, the receivers require extensive signal processing capabilities in order to detect the data in the presence of the unwanted signals. This represents a task of considerable complexity. As such, it may not be possible to detect the data in real time, because state of the art signal processors are not able to execute the number of calculations required for the signal processing algorithms before the data must be presented at an output. However, it is not always necessary to solve signal processing problems exactly. It is known to be possible to only compute an approximation of the exact solution without degrading the overall performance of the system. Computing an approximation of the solution reduces the amount of time spent solving the problem, reduces the amount of hardware required for implementing the algorithm, reduces the power consumption of the device, and in some case makes it possible to achieve real-time behavior in the first place.
A part of a process which is most appropriate for detecting data communicated in accordance with a code division multiple access system requires the factorization or decomposition of a correlation matrix. In order to effect real-time operation with known signal processors, it is necessary to provide an approximation to an exact solution of a factorization of this correlation matrix. In an article entitled "Real-time Feasibility of Joint Detection CDMA", by J. Mayer, J. Schlee and T. Weber, Proceedings of the Second European Personal Mobile Communications Conference, Bonn, Germany, September 1997, pages 245 to 252, an approximation of a matrix factorization is described using a known numerical approximation process. However, the computational effort needed to perform this multi-user detection is still considerable.
A technical problem therefore exists in further reducing the computational complexity, or correspondingly increasing the accuracy which can be achieved using an approximation method to generate factors of a matrix.